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  2. Ideogram (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

    Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The model is capable of generating legible text in the images compared to other text-to-image models. [1] [2]

  3. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.

  4. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    A text-to-image prompt commonly includes a description of the subject of the art, the desired medium (such as digital painting or photography), style (such as hyperrealistic or pop-art), lighting (such as rim lighting or crepuscular rays), color, and texture. [51] Word order also affects the output of a text-to-image prompt.

  5. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

  6. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [129] and reweighting training data. [130]

  7. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom.

  8. Artificial intelligence art - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_art

    The website Artbreeder, launched in 2018, uses the models StyleGAN and BigGAN [56] [57] to allow users to generate and modify images such as faces, landscapes, and paintings. [58] In the 2020s, text-to-image models, which generate images based on prompts, became widely used, marking yet another shift in the creation of AI generated artworks. [2]

  9. Midjourney - Wikipedia

    en.wikipedia.org/wiki/Midjourney

    To generate images, users use the /imagine command and type in a prompt; [23] the bot then returns a set of four images, which users are given the option to upscale. To generate images on the website, users initially needed to have generated at least 1,000 images through the bot; this limitation has since been removed.

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